Choose the best training program according to your career.
Improve the performance of your business with our innovative Industrial Training Program.
Read More →
Our instructor-led training classes are designed to make you an expert.
Read More →
Real-life case studies are a great way to demonstrate your practical knowledge.
Read More →
Explore blogs, latest technologies and industry updates with practical examples.
Read More →
Browse all available training programs and choose the right one for your career.
Read More →Know more about who we are and what we stand for.
Discover our mission to equip individuals with essential IT skills and industry expertise.
Read More →Learn, practice and plan your career — bilkul free.
Book a free video counselling session and pick the right course for you.
Read More →Learners in Noida can sign up for Uncodemy's 5–6 month instructor-led live online RAG Engineering program. The syllabus covers document ingestion & chunking, embeddings, vector databases, retrieval pipelines, hybrid search and production RAG deployment. Geared toward developers, data scientists/ML engineers and aspiring AI engineers, the program offers 13 modules, 90+ live sessions, 140+ hours and an enterprise RAG capstone. Fee: ₹17,500 + 18% GST, total ₹20,650. EMI starting from ₹4,032/month.
Learn from 8+ years experienced professionals
Build real Playwright test suites, not just theory
Get lifetime access to recorded sessions & materials
Resume Building, Mock Interviews & Job Support
Certificate of Completion from Uncodemy
Weekday & Weekend Online & Offline
On completing the RAG Engineering training program, Uncodemy learners acquire practical skills in document processing, embeddings, vector databases, retrieval pipelines and hybrid search. After finishing their training and career preparation, eligible learners can apply for positions like RAG Engineer, AI Application Engineer and GenAI Engineer. Placement records for Noida learners are updated regularly — verified outcomes are published at uncodemy.com/placement.
RAG Engineering (Retrieval-Augmented Generation) is the discipline of integrating large language models with external knowledge retrieval, so that responses rest on real, up-to-date enterprise data rather than relying only on what the model learned during training. It spans document ingestion, chunking, embeddings, vector databases and retrieval pipelines that supply relevant context to an LLM at query time — reducing hallucination and empowering AI systems to answer questions about private, domain-specific or frequently changing information.
What does a RAG engineer do? A RAG engineer handles document ingestion and chunking, creates embeddings and maintains vector databases, designs retrieval pipelines, implements hybrid search, gauges RAG accuracy, and deploys production RAG systems. Day-to-day tasks include Python scripting, using frameworks like LangChain and LlamaIndex, tuning chunking and retrieval strategies, measuring relevance and faithfulness, and exposing RAG-powered APIs for applications to use.
Where RAG Engineering is concerned with building retrieval-grounded AI systems on enterprise knowledge, LLM Engineering encompasses LLM-powered applications broadly and Generative AI centres on autonomous agents.
| Aspect | RAG Engineering | LLM Engineering | Generative AI |
|---|---|---|---|
| Core focus | Building retrieval-grounded AI systems on enterprise knowledge | Building, fine-tuning & deploying LLM-powered applications broadly | Building GenAI apps + autonomous AI agents |
| Coding depth | High | High | Moderate to High |
| Typical entry salary | ₹5–9 LPA (Entry-Level RAG Engineer) | ₹6–10 LPA (per LLM Engineering course sheet) | [CONFIRM per GenAI course sheet] |
| Uncodemy program duration | 5–6 months | 5–6 months | ~3–4 months (indicative) |
Salary ranges are indicative and vary by role, skills, experience, location and employer.
A 5–6 month live online program, the RAG Engineering course is structured across 90+ live sessions and 140+ hours of learning. It contains 13 modules that guide learners from RAG & enterprise knowledge AI foundations through Python for RAG engineering, LLM fundamentals & API integration, document processing & data ingestion, text chunking & document transformation, embeddings & semantic search, vector databases & indexing, RAG, advanced retrieval & reranking, hybrid search & knowledge retrieval, RAG evaluation & optimization, production RAG APIs & deployment, and a 20-hour enterprise RAG capstone. Practical exercises with real tools appear in each module, and the program culminates in hands-on RAG projects and an enterprise capstone. It is delivered fully live online for Noida and nationwide learners.
Who should join this course:
Eligibility: It helps to have programming fundamentals, though they are not required — Python is covered beginning in Module 2. Familiarity with basic LLM concepts gives you an edge, but these are gradually introduced from Module 3. For practical sessions, a laptop with consistent internet is essential.
Choose a batch timing that best fits your schedule. Live online batches, IST timings. Reserve a free demo class first-hand, or step into our upcoming weekend and weekday live batches — suited to working professionals as well as students, with flexible timings and hands-on training.
| Date | Time | Trainer | Seats Left |
|---|---|---|---|
| 16oct | 07:30 PM – 08:30 PM | Mr. Irshad | 01Seat |
| 22oct | 02:00 PM – 03:00 PM | Mr. Upendra Kumar Tiwari | 02Seats |
| 26oct | 10:30 AM – 11:30 AM | Mr. Irshad | 01Seat |
| 30oct | 12:00 PM – 01:00 PM | Mr. Upendra Kumar Tiwari | 02Seats |
| Date | Time | Trainer | Seats Left |
|---|---|---|---|
| 27oct | 03:00 PM – 05:00 PM | Mr. Irshad | 02Seats |
8+ new batches start every month. All timings are in IST. Seats are limited and updated daily.
The syllabus is structured over 13 modules that cover 140 hours. The sequence is modelled on how RAG engineering works in reality: foundations → Python → LLM fundamentals & API integration → document processing & chunking → embeddings & semantic search → vector databases → RAG → advanced retrieval/reranking → hybrid search → evaluation → production deployment → capstone. Every module includes practical exercises with real tools, and the program culminates in hands-on RAG projects and an enterprise RAG capstone.
| # | Module | Hours | Tools |
|---|---|---|---|
| 1 | RAG & Enterprise Knowledge AI Foundations | 8 | Python, LLM APIs |
| 2 | Python for RAG Engineering | 10 | Python, Git |
| 3 | LLM Fundamentals & API Integration | 10 | OpenAI APIs, Hugging Face |
| 4 | Document Processing & Data Ingestion | 8 | Python, LlamaIndex |
| 5 | Text Chunking & Document Transformation | 8 | LangChain, LlamaIndex |
| 6 | Embeddings & Semantic Search | 10 | Hugging Face, OpenAI Embeddings |
| 7 | Vector Databases & Indexing | 10 | FAISS, ChromaDB, Pinecone, pgvector |
| 8 | Retrieval-Augmented Generation (RAG) | 12 | LangChain, LlamaIndex, Vector DBs |
| 9 | Advanced Retrieval & Reranking | 10 | LangChain, Cross-Encoders |
| 10 | Hybrid Search & Knowledge Retrieval | 10 | Elasticsearch/OpenSearch, LangChain |
| 11 | RAG Evaluation, Accuracy & Optimization | 12 | RAGAS, LangSmith, Python |
| 12 | Production RAG, APIs & Deployment | 12 | FastAPI, Docker, Cloud Deployment Tools |
| 13 | Enterprise RAG Projects & Capstone | 20 | All tools |
| Total | 140 Hours | 15+ tools | |
On finishing all 13 modules, the assignments and the Enterprise RAG capstone project, you receive the Uncodemy RAG Engineering Program Certificate. The certificate mentions the program name, duration, tools covered and completion date. It is verifiable online at certificate.uncodemy.com and provides a record of successful completion of the Uncodemy RAG Engineering program.
The certificate is linked to the practical work completed during the program — including hands-on RAG pipeline work, retrieval evaluation and the 20-hour Enterprise RAG capstone project. Learners gain hands-on exposure to Python, OpenAI APIs, Hugging Face, LangChain, LlamaIndex, LangGraph, FAISS, ChromaDB, Pinecone, PostgreSQL/pgvector, Elasticsearch/OpenSearch, FastAPI, Docker, Git/GitHub and cloud deployment tools.
This is an independent Uncodemy certificate. It is not affiliated with, endorsed by, or a credential of OpenAI, Pinecone or any other RAG/vendor provider whose tools are taught in this course. Certificate verification process pending confirmation.
Uncodemy Certificate Verification Online Certificate Verification & Download certificate.uncodemy.com_2.webp)
_3.webp)
OpenAI APIs
LangChain
LlamaIndex
Vector Databases
Hugging Face
FAISS
ChromaDB
Pinecone
FastAPI
Docker
Elasticsearch
Git & GitHub
Uncodemy is a career-focused IT training institute run by Uncodemy Edutech Pvt. Ltd. With 14+ years of training excellence, classroom centres in Delhi and Noida, and live online classes reaching learners across India, Uncodemy delivers instructor-led training for emerging technologies.
Within this RAG Engineering program, learners build retrieval pipelines, hybrid search systems and production RAG APIs, and complete an enterprise RAG capstone project. The training addresses the way retrieval-grounded AI systems are engineered in production — document processing, embeddings, vector search, retrieval evaluation and deployment. You can browse the full module-by-module curriculum before you enrol.
In addition to training, Uncodemy offers instructor-led sessions, practical assignments, project-based learning, interview preparation and career support. What that support includes — and what it does not — is defined in our career support policy, together with the eligibility conditions published before enrolment rather than after payment.
If you are still deciding on a direction, Uncodemy also runs LLM Engineering, AI Testing and Data Science courses for Noida and Maharashtra learners.
Portfolio/capstone project review:Your hands-on RAG pipelines, retrieval evaluation work and enterprise RAG capstone are reviewed and refined into a portfolio an interview will find credible.
Resume & LinkedIn:We build your resume around RAG engineering keywords and measurable outcomes, and align your LinkedIn profile to match.
Interview preparation:Retrieval pipeline design questions, chunking-strategy trade-offs, evaluation-metric discussions and RAG engineering case studies specific to AI hiring.
Mock interviews:Sessions with industry trainers, followed by written feedback on what to fix.
Opportunity sharing:Relevant openings from our hiring network of 850+ companies are shared with you, with support through the application and interview process.
Continued support:This is active assistance, not a guarantee of employment — no training institute can honestly promise a job. Support continues after your program ends for learners who stay engaged with the process.
The people who actually teach this course
Irshad Khan, Senior Trainer at Uncodemy, leads this program, bringing 8+ years across Data Science, Data Analytics, SQL, Power BI, Python and Generative AI. He's also the one who reviewed and approved the curriculum you see here.
Most institutes blur two jobs into one; Uncodemy keeps them apart. Trainers handle the live teaching. A separate group of domain reviewers — specialists who never teach the batch — check that the curriculum stays accurate and up to date. Upendra Kumar Tiwari reviews the technical content for this program, so the person teaching it isn't the only one vouching for it.
Uncodemy publishes every trainer and domain reviewer by name, along with their area of focus and background — so you can check them out before enrolling, not afterward.
Senior Data Science Trainer
Expertise15+ years of industry experience building production machine learning systems for retail, telecom and consulting teams.
Modelling security breaches in iOS apps, dormant customer prediction and factor analysis, last-mile delivery optimisation, and credit card fraud detection.
Data Analytics & AI Trainer
ExpertisePython · SQL · Machine Learning · Tableau · Artificial Intelligence · Deep Learning · Power BI · MLOps
8+ years across consulting and public-sector analytics, with deep hands-on work in AI and MLOps delivery.
Built an OCR model, a disease-prediction model, and a fraud-control model deployed across every Indian state under the Ministry of Health & Welfare.
Data Analytics & AI Trainer
ExpertiseExcel, SQL, Python, statistics, Power BI, Tableau and Generative AI
7+ years turning aviation and enterprise data into forecasting models, dashboards and AI assistants.
AI agent chat/voice bot, AI-driven data analysis, a sales-forecasting ML model, NPS data model evaluation, and a face-recognition model for biometrics.
Data Analytics Trainer
ExpertisePython · SQL · Excel · Power BI · Tableau · ML · DL · NLP · Time Series · IoT Devices · Prompt Engineering · Chatbots
5+ years in logistics and consumer-brand analytics, with a strong focus on time series, NLP and applied automation.
Speech-to-text using core NLP (T2S), talent acquisition research, and product launch & CMS work on keventers.com using Sparktech.
Data Analytics Trainer
ExpertiseAdvanced Excel · SQL · Power BI · Tableau · Python · Data Visualisation · Statistics
Trainer for the analytics and business intelligence track at Uncodemy, working with learners on Excel, SQL and BI tooling from first principles to interview-ready projects.
Guides classroom capstones on sales and customer dashboards, KPI reporting and end-to-end data cleaning workflows.
Data Analytics Trainer
Expertise
Data Analytics Trainer
Expertise
MD & CEO
ExpertiseFounder, MD & CEO of Uncodemy and GS Net Academy, with experience in education, technology leadership, research, mentorship and career development.
Leads strategic direction, academic initiatives, technology-driven education programs and mentorship across Uncodemy and GS Net Academy.
Data Analytics Trainer
Expertise
MD & CEO
ExpertiseFounder, MD & CEO of Uncodemy and GS Net Academy, with experience in education, technology leadership, research, mentorship and career development.
Leads strategic direction, academic initiatives, technology-driven education programs and mentorship across Uncodemy and GS Net Academy.
CEO & Founder
ExpertiseCEO & Founder of GvCloud Secure and Uncodemy with 14+ years of professional experience building scalable web, mobile and AI-driven solutions for clients across India, USA, UK, Canada, Australia and Singapore.
Leads technology strategy, scalable web and mobile solutions, AI-driven products and EdTech initiatives across Uncodemy and GvCloud Secure.
Enrol in Uncodemy's RAG Engineering course, designed for learners in Noida, right away! Build practical capabilities in document processing, embeddings, vector databases, retrieval pipelines and hybrid search via instructor-led live online training, hands-on projects and an enterprise RAG capstone. Start your RAG engineering journey with structured training and career preparation.
| Role | Core Tools |
|---|---|
| RAG Engineer | LangChain, LlamaIndex, Vector DBs, Python |
| AI Application Engineer | LangChain, FastAPI, Vector DBs |
| GenAI Engineer | OpenAI APIs, LangChain, Embeddings |
| LLM/RAG Engineer | LangChain, LlamaIndex, Evaluation Tools |
| AI Solutions Engineer (Junior) | FastAPI, Docker, Cloud Deployment Tools |
| Search/Retrieval Engineer | Elasticsearch/OpenSearch, Vector DBs, Python |
| Role | Salary Range |
|---|---|
| Entry-Level RAG Engineer | ₹5–9 LPA |
| RAG / GenAI Engineer | ₹8–15 LPA |
| AI Application Engineer | ₹8–16 LPA |
| LLM / RAG Engineer | ₹10–20 LPA |
| Senior RAG Engineer | ₹18–30 LPA |
| AI Solutions Engineer | ₹15–28 LPA |
| Lead AI / RAG Engineer | ₹25–40 LPA |
| Factor | This Program |
|---|---|
| Duration | 5–6 months |
| Learning hours | 140+ |
| Live sessions | 90+ |
| Tools | 15+ |
| Capstone | 20-hour Enterprise RAG project |
| Career support | Dedicated Career & Placement Assistance |
| If you want... | Recommend |
|---|---|
| Full RAG Engineering career transition | This program |
| Already know LLM Engineering fundamentals, want to specialise in retrieval systems | This program |
| Building AI agents specifically | Consider Generative AI & Agentic AI course |
| Broad LLM application development | Consider LLM Engineering course |
The program runs for 5–6 months and includes 140+ hours of learning across 90+ live sessions. Weekday and weekend batches are both available.
Programming fundamentals are helpful but not mandatory — Python is taught from Module 2 onward. Familiarity with basic LLM concepts is a plus but built up in Module 3. A laptop with stable internet is required.
15+ tools including Python, OpenAI APIs, Hugging Face, LangChain, LlamaIndex, LangGraph, FAISS, ChromaDB, Pinecone, PostgreSQL/pgvector, Elasticsearch/OpenSearch, FastAPI, Docker, Git/GitHub and cloud deployment tools.
Yes. Module 7 covers Vector Databases & Indexing (10 hours) and Module 10 covers Hybrid Search & Knowledge Retrieval (10 hours). Both are core components with hands-on exercises.
The capstone is Module 13: Enterprise RAG Projects & Capstone (20 hours). You build an end-to-end RAG application applying document processing, embeddings, vector search, retrieval, evaluation and deployment.
All 90+ sessions are live and instructor-led, with recordings available afterwards for revision.
The program fee is ₹17,500 plus 18% GST. Total fee is ₹20,650. The same fee applies in all modes and cities.
EMI starts from ₹4,032 per month. The exact amount, tenure and eligibility depend on the applicable payment or financing option — a counsellor can confirm your plan.
Yes. You can attend a demo session to see the teaching style, meet the trainer and review the curriculum before deciding. Contact us to book a demo.
We provide Dedicated Career & Placement Assistance — resume building, LinkedIn optimisation, portfolio review, interview preparation, mock interviews and opportunity sharing through our network of 850+ companies. We do not guarantee employment.
Entry-level RAG Engineer roles in the market range around ₹5–9 LPA (indicative). Outcomes vary by skills, experience, employer and market conditions. Uncodemy does not guarantee any specific salary or employment outcome.
Indicative market ranges: Entry-Level ₹5–9 LPA, RAG/GenAI Engineer ₹8–15 LPA, Senior RAG Engineer ₹18–30 LPA, Lead AI/RAG Engineer ₹25–40 LPA. Actual offers vary by role, skills, experience, employer and market conditions. Uncodemy does not guarantee any specific salary.
RAG Engineer, AI Application Engineer, GenAI Engineer, LLM/RAG Engineer, AI Solutions Engineer (Junior) and Search/Retrieval Engineer.
Developers wanting to specialise in retrieval-grounded AI systems, data scientists/ML engineers upskilling into RAG engineering, aspiring AI engineers, and working professionals moving into GenAI/RAG roles.
Statistics are based on Uncodemy's internal records and publicly available review-platform information. Placement and salary outcomes vary by learner, skills, experience, location, employer and market conditions. Career and placement assistance does not constitute a guarantee of employment or a specific salary package.
This course is delivered live online nationwide, including for Noida learners. Classroom training is available at our Delhi and Noida centres for other courses. Noida learners typically join live online.
No. This is an independent Uncodemy certificate. It is not affiliated with, endorsed by, or a credential of OpenAI, Pinecone or any other RAG/vendor provider whose tools are taught in this course.
Uncodemy
Retrieval-Augmented Generation project designed to retrieve relevant information from knowledge sources and generate context-aware AI responses.
Python
Pandas
Jupyter
GitHub
Uncodemy
AI knowledge management system designed to organize information into a searchable knowledge base and retrieve relevant context for intelligent answers.
SQL
Python
GitHub
CSV
Uncodemy
AI research assistant designed to retrieve relevant information, organize research content, and help users generate useful insights from sources.
Jupyter
Pandas
Python
GitHub
Uncodemy
Document-focused RAG assistant designed to retrieve information from uploaded content and provide context-aware answers based on relevant documents.
SQL
Pandas
GitHub
Python
Uncodemy
AI-powered developer documentation assistant designed to retrieve relevant code information and make software documentation easier to understand.
Python
GitHub
SQL
Jupyter
Uncodemy
Retrieval-Augmented Generation project designed to combine relevant information retrieval with AI-generated responses for more context-aware results.
Pandas
Python
CSV
GitHub
Uncodemy offers its RAG Engineering program to learners across Noida through flexible learning options, including live online classes that can be attended from anywhere and classroom training at Uncodemy’s Noida centre, located at B, 14-15, Udhyog Marg, Block B, Sector 1, Noida, Uttar Pradesh 201301. The centre is conveniently located near Noida Sector 15 Metro Station, making it accessible for learners from Noida and nearby areas. Students can join the same RAG Engineering batches with experienced trainers, a practical curriculum, hands-on RAG projects, and structured career support, whether they choose classroom or live online learning.
4.7/5 (500+)
5/5 (30+)
4.7/5 (500+)
5/5
4/5 (130+)
5/5 (54+)
